Thank you so much for the new release! Always a great job, You all do.
I did some rendering test on an old project of mine using
"CinGG-20241231-alternative_shortcuts.AppImage"; only 10 secs by
selection (highlight) in Timeline.
Render setup: vp9_1280x270_24or24or50fps.webm
- Info by terminal says: 300 frames 94.918 secs 3.161 fps; File Size
1.6MB
An old Cin version, same setup,...
- Info by terminal says: 300 frames 83.582 secs 3.589 fps; File Size
1.5MB
I think, it is strange that rendering of an old version of CinGG is
slightly faster than a new one. Is it, probably, due to the old Laptop
and old Operating System that adapts better?
IgorBeg
Il 31/12/2024 21:14, Phyllis Smith via Cin ha scritto:
AppImages available for the December 2024 release at:
https://cinelerra-gg.org/download/images/
+
https://cinelerra-gg.org/download/images/CinGG-20241120-x86_64-IntelHW.AppImage
Packages available for the newer operating systems at:
https://github.com/einhander/cin-gg-packages/releases/tag/20241229
See latest release notes below the *****.
Question for *Andrey*:
Would it be possible to easily add --with-onevpl to the configure
line in your build script for Leap 15.5 RPM package?
It would require the added package of "oneVPL-devel" to be installed
on that O/S (that is the package name for Fedora).
If you use the same build script on all of your package builds, they
would have to have "oneVPL-devel" installed also. I have tested the
build on Fedora 40 after installing that package and had no problem. I
have none of the new Intel hardware to test but Terje would like to be
able to use these new Intel hardware/software features on his
computer. It should not impact normal usage (hopefully).
********* GIT for Cinelerra-GG has the following changes from
11/01/2024-12/31/2024 *********
*SVT_AV1* has been upgraded to 2.3.0 from 2.2.1 with no known problems.
*Nvidia encode headers* updated from 10.0.26.0 to 12.2.72.0 which
corresponds to Video Codec SDK
version 12.0.16. The required driver version for Linux is 550.54.14
or newer. You can check to see
if your Nvidia graphics board is supported at this website at the
time of this release:
https:://developer.nvidia.com/video-encode-and-decode-gpu-support-matrix-new
<http://developer.nvidia.com/video-encode-and-decode-gpu-support-matrix-new>
There may be user impact since the previous required driver for
Linux was 445.87.
Minor addition to add non-working ffmpeg filters to plugin.opts; these
are blacklisted items.
_Andrew-R contributions_
The build for *NetBSD* 10.0/amd64 is now working with 3 patches
applied and checked in.
New *Termux* (Android) encoding render formats have been added:
h264_mediacodec.mp4,
hevc_mediacodec.mp4, and mpeg2_hdv.mpeg. The 2 mediacodec formats
will only work on Android
(mediacodec is part of the Android low-level multimedia support
infrastructure).
A mod to mjpegtools disables compilation of y4mdenoise to prevent
compiler errors in *clang*.
_Terje testing/building and Andrew-R diagnosing contributions_
12 *new render formats* for qsv, which can be used only if you have
that particular Intel hardware and
software, have been added as developed/tested by Andrew and Terje.
(QSV is Intel’s Quick Sync Video for its dedicated video
encoding/decoding hardware core.)
12 *new or replaced vaapi hardware encoding *render formats are now
available. Run the vainfo
program to determine what formats your hardware/software recognizes.
There are some patches to ffmpeg.C and ffmpeg.h to support the above.
Additions for building with *oneVPL* (Intel’s oneAPI Video Processing
Library) is now an option to be
enabled if desired - not enabled by default - on the autogen line by
adding “--with-onevpl”.
Note in reference to the previous paragraph:
There should be no impact to standard usage of CinGG but users need
to be especially aware of the
fact that using a render encoding format that requires specific
hardware/software implementation
will give an error. In addition, the standard AppImage releases will
not provide the availability to use
specific hardware features. This is the same as the inability to use
vdpau/vaapi from those same
appimages since they are created on a computer without the end users
specific hardware.
An *AppImage* has been graciously created for users who do have the
Intel hardware that supports
these newly tested/implemented features *of oneVPL, av1, qsv, and
vaapi* for download at:
https://cinelerra-gg.org/download/images/CinGG-20241120-x86_64-IntelHW.AppImage
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